Method for preventing tampering of electric power internet of things sensing data of cascaded codes

Abstract

The invention discloses a method for preventing tampering of electric power internet of things sensing data of cascaded codes, and belongs to the field of data processing. According to the method, the characteristic advantages of cascade connection of the RS codes and the convolutional codes are fused, the grading strategy of triggering the RS codes on demand is adopted, the optimized convolutional decoding algorithm is matched, and on the premise that calculation and transmission expenses are not remarkably increased, the requirement of an electric power internet-of-things scene for real-time transmission and the core target of data reliability are considered. Meanwhile, the improved Viterbi algorithm is used, values of other branch metrics are rapidly calculated through symmetry and a logic relation, and therefore the convolutional code decoding efficiency is improved. Besides, an optimized search algorithm is used, and based on path measurement characteristics of Viterbi decoding, error positions are subjected to probability sorting and a search sequence is optimized, so that the efficiency of RS code decoding error correction is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of data processing, and particularly relates to a power internet of things sensor data tamper-proofing method based on concatenated codes. BACKGROUND

[0002] Due to the deep dependence of the power internet of things on information systems, the security risks thereof are significantly increased, and the power internet of things is easily attacked. From the architecture composition dimension, the core structure of the power internet of things can be divided into four key levels, which are a perception layer, a network layer, a platform layer and an application layer. At present, the information security research of the power internet of things mainly focuses on the network layer, however, the sensor devices of the perception layer also have significant security risks. In the signal transmission link of the sensor, each component has a default trust attitude for the authenticity and validity of the received input, and such unfiltered trust mechanism undoubtedly creates an exploitable opportunity for attackers.

[0003] In the power internet of things, digital sensors generally use parity check, cyclic redundancy check and other methods to detect errors in data transmission, but these methods can only identify errors and cannot repair error data, and can only rely on the sending end to retransmit data. In order to realize effective error correction of data, various coding technologies are introduced in the industry, but they also have limitations: the grouping code algorithm is simple but the performance is far from the Shannon limit; the convolution code is easy to implement but the decoding efficiency is low; the RS code is strong in burst error resistance, but direct use when the channel error probability is low will lead to resource redundancy and time delay, and the system resource utilization rate is not high.

[0004] In the prior art, the RS code has strong error correction capability for burst errors, but when the channel error probability is low, it will lead to redundant operation resources and additional time delay. In addition, the traditional concatenated code scheme forcibly executes the complete encoding process regardless of the error rate, which will bring unnecessary overhead in the low error rate scenario, and the system has insufficient dynamic adaptability. SUMMARY

[0005] The application provides a power internet of things sensor data tamper-proofing method based on concatenated codes, which uses RS convolution concatenated codes to dynamically trigger RS code to correct burst errors on the basis of convolution code correcting random errors. The data is first convolution encoded, and then the original power internet of things sensor data is RS encoded and convolution encoded again when the check fails, and the receiving end restores the data in combination with the decoding results of the two times. Through the application, the data is anti-tampered and self-recovered under mixed errors, and the real-time performance, reliability and resource consumption are balanced.

[0006] The application provides a power internet of things sensor data tamper-proofing method based on RS convolution concatenated codes, which realizes the anti-tampering and error self-recovery of power internet of things sensor data without significantly increasing the calculation and transmission overhead, and ensures the integrity of the data in the mixed error environment.

[0007] The application discloses a power internet of things sensor data tamper-proofing method based on concatenated codes, which comprises the following steps:

[0008] Step 1: original power internet of things sensor data convolutional encoding stage;

[0009] Transmitting end: convolutional encoding of the data collected by the power internet of things sensor, and sending the data to the receiving end together with the accumulated sum and state bit information;

[0010] Receiving end: receiving the data sent by the transmitting end.

[0011] Step 2: convolutional decoding and RS precoding stage;

[0012] Transmitting end: RS encoding of the data, convolutional encoding of the obtained check code word, and temporary storage of the convolutional encoded data in the transmitting end;

[0013] Receiving end: immediately performing convolutional decoding after receiving the data, and correcting the random errors possibly occurring in the transmission process by using the convolutional code.

[0014] Step 3: error correction result feedback stage;

[0015] Receiving end: checking the convolutional decoding result by means of the received accumulated sum. If the accumulated sum of the original power internet of things sensor data received by the receiving end is different from the accumulated sum of the data obtained by the convolutional decoding, the receiving end delivers a decoding failure feedback signal to the transmitting end, prompting the transmitting end to continue sending RS encoded data for secondary error correction.

[0016] Transmitting end: setting a waiting period, and transmitting the RS encoded data as soon as the decoding failure feedback signal from the receiving end is obtained within the waiting period. If the decoding failure feedback signal from the receiving end is not obtained within the set waiting time, it is determined that no error occurs in the data transmission or the error is corrected by the convolutional decoding operation of the receiving end.

[0017] Step 4: RS decoding and error correction stage;

[0018] Receiving end: decoding the received sequence by using the convolutional code mode, concatenating the convolutional decoding sequence, and performing RS decoding and error correction;

[0019] Transmitting end: waiting for the receiving end to complete the data error correction.

[0020] Further, the specific method for the transmitting end to perform convolutional encoding on the original power internet of things sensor data in step 1 is as follows:

[0021] information bits are encoded into bits, and the convolutional code is denoted as ​N represents the constraint length of the convolution code; in The input bit at time The output code word is C i (1) , C i (2) ;

[0022] The generating polynomial of the first code word is:

[0023] ;

[0024] The generating polynomial of the second code word is:

[0025] ;

[0026] is the variable of the generating polynomial;

[0027] Subsequently, the next bit is encoded by using the same method as above, and the above steps are repeated to obtain the code group after convolution encoding of the information sequence.

[0028] Further, the step 2, the sender encodes the original power Internet of Things sensing data by using RS encoding:

[0029] Let the information polynomial of a group of data to be encoded be:

[0030] ;

[0031] represents the binary value of the k-1th bit of the to-be-encoded group;

[0032] For the RS(n, k) code on a finite field, the generating polynomial g(x) is:

[0033] ;

[0034] Then, the encoding process of the RS code, i.e., the generating process of the check polynomial r(x) is:

[0035] ;

[0036] represents the modulo-2 operation;

[0037] Taking as the code element, the final encoding polynomial is obtained:

[0038] .

[0039] Further, the method for correcting random errors that may occur in the output transmission process by using the convolution code in step 2 is specifically:

[0040] Step 2.1: Optimize the calculation process of branch metrics:

[0041] If the input information bit is m i , the encoded output result is C1 and C2; if the input information bit becomes ~m i , the encoded output will be converted to and respectively; assuming that the decoding input is X1, X2, and the state S i (2j) transfers to the state S i+1 (j) at the i+1 moment, the branch metric of the transition process is:

[0042] ;

[0043] The superscript j represents the index value, which is used to represent the unique transition relationship formed by a specific input bit, represents the XOR operation;

[0044] When the condition of “same state, different input bits” is met, the state S i (2j) transfers to S i+1 (8+j) , and the branch metric of S i+1 (8+j) is:

[0045] ;

[0046] The values of the other three branch metrics are calculated through symmetry and logical relationship:

[0047] ;

[0048] Step 2.2: Optimize the storage of path information during backtracking decoding:

[0049] When optimizing the storage of path information during backtracking decoding, the structural characteristics of convolution code should be relied on. First, in the current state, the smaller path metric is selected and retained as the better path. Second, the path information stored in the previous state is retrieved, and a left shift operation is performed on it, and then the highest bit data of the current state is filled into the lowest bit of the information to complete the iteration of the path information. Finally, the updated path information is stored in the storage area corresponding to the current state, completing a storage optimization.

[0050] Further, the method for judging decoding errors in the error correction result feedback stage of step 3 is:

[0051] Step 3.1: judging whether error occurs:

[0052] Let the received polynomial be and the transmitted polynomial be

[0053] ;

[0054] and the error polynomial be

[0055] If the received codeword is error-free, the received polynomial should be divisible by the generator polynomial g(x) of the RS code, otherwise, it means that the received data has error.

[0056] Step 3.2: judging error position: based on the path metric characteristics of Viterbi decoding, the error position is probabilistically sorted and the search order is optimized, and the error position polynomial and error value polynomial are solved by the receiver to locate the error position.

[0057] Further, the specific method of step 3.2 is:

[0058] Step 3.2.1: extracting path metric characteristics;

[0059] In the Viterbi decoding process, after every time,

[0060] First, calculate the path metric increment, that is, after every time, the path metric of the current shortest path is subtracted from the path metric of the shortest path at several time points , and the difference is the path metric increment ; secondly, calculate the path difference, that is, first determine the current shortest path and another path , and then calculate the path metric difference of the two paths, which is the path difference .

[0061] Step 3.2.2: locating safe positions and unsafe positions;

[0062] When the path difference is 2 and the path metric increment is 0, the error rate of the corresponding byte is the lowest, and such positions are defined as safe positions, and the remaining positions are defined as unsafe positions; and according to the combination of path metric increment and path difference, the unsafe positions are sorted from high to low according to error probability;

[0063] Step 3.2.3: iterative search; ​

[0064] The arrangement threshold value is set to distinguish the high probability error area from the second high probability error area, the priority order is set as: high probability error area > second high probability error area > safe position; and the elements are substituted into the error position polynomial in the priority order according to the priority order, whether it is a root is judged; if the element is a root, the error position is found;

[0065] Step 3.2.4: error value calculation and error correction;

[0066] For the searched error position, the error value is calculated by using the error value polynomial algorithm, and the error value is deducted from the received sequence to recover the original power internet of things sensing data.

[0067] The application fuses the characteristics and advantages of RS code and convolution code cascade, adopts a hierarchical strategy of "on-demand triggering RS coding", and is matched with an optimized convolution decoding algorithm, so that the core target of "real-time transmission" demand and "data reliability" of the power internet of things scene is considered under the premise of not significantly increasing the calculation and transmission overhead. At the same time, the improved Viterbi algorithm is used to quickly calculate the values of other branch metrics through symmetry and logical relationship, thereby improving the decoding efficiency of the convolution code. In addition, the optimized search algorithm is used to sort the error positions based on the path metric characteristics of the Viterbi decoding and optimize the search order, thereby improving the efficiency of RS code decoding and error correction. BRIEF DESCRIPTION OF DRAWINGS

[0068] Figure 1 It is a feedback type cascade code flow chart.

[0069] Figure 2 It is a convolutional encoding principle schematic diagram.

[0070] Figure 3 It is a Viterbi decoding principle schematic diagram.

[0071] Figure 4 It is a butterfly processing unit schematic diagram.

[0072] Figure 5 It is a path information storage schematic diagram.

[0073] Figure 6 It is a normal image feedback type RS-convolutional cascade code effect diagram.

[0074] Figure 7 It is a coding error image feedback type RS-convolutional cascade code effect diagram.

[0075] Figure 8 It is a coding error correction image feedback type RS-convolutional cascade code effect diagram. DETAILED DESCRIPTION

[0076] The specific steps of the convolutional coding stage of the original power IoT sensor data are as follows:

[0077] (1) The transmitting end performs convolutional encoding on the original power IoT sensor data.

[0078] (2) The transmitting end retains the end state value of the convolutional encoding of the original power IoT sensor data, calculates the cumulative sum of the original power IoT sensor data, and sends the above information to the receiving end.

[0079] (3) The receiving end receives the data from the sender.

[0080] In step (1) of the convolutional coding stage of the original power IoT sensor data, the specific steps of convolutional coding are as follows:

[0081] Convolutional codes are often denoted as ,Will Each information bit is encoded One bit. The method used in this study... The principle of convolutional codes is as follows: As shown, in Input bits at any time The output codeword is C. i (1) C i (2) .

[0082] The generator polynomial of the first codeword is:

[0083]

[0084] The generator polynomial of the second codeword is:

[0085] .

[0086] Then, all registers perform a right shift operation, inputting the next bit. Repeating this process will eventually yield the convolutional coding result of the information sequence.

[0087] The specific steps of the convolutional decoding and RS precoding stages are as follows:

[0088] (1) The transmitting end performs RS encoding on the collected power IoT sensor data sequence.

[0089] (2) The transmitting end performs convolutional encoding on the check codeword obtained by RS encoding. The data after convolutional encoding is temporarily stored at the transmitting end.

[0090] (3) The receiving end performs decoding and error correction of the convolutional code.

[0091] In step (1) of the convolutional decoding and RS precoding stage, the specific steps of RS encoding are as follows:

[0092] Let the information polynomial corresponding to a set of data to be encoded be:

[0093] ;

[0094] The generator polynomial g(x) takes the following values:

[0095] ;

[0096] The generation process of the verification polynomial r(x) can be represented as:

[0097] ;

[0098] Using r(x) as the code element, the final encoded polynomial is obtained as follows:

[0099] ;

[0100] In step (3) of the convolutional decoding and RS precoding stage, the specific principle of the improved Viterbi algorithm is as follows:

[0101] (1) Optimize the calculation process of branch metric:

[0102] The principle of Viterbi decoding is as follows: The process involves finding a path among the many paths shown that minimizes the Hamming distance between the output encoded through that path and the received sequence. The core operation for locating the surviving path can be represented using the butterfly operation unit shown in Figure 4.

[0103] When the input information bits are m i hour ， This indicates that state S i (2j) With S i+1 (j) Branching measure of the relationship between for:

[0104] ;

[0105] Where X1 and X2 are decoding inputs, and C1 and C2 are encoding outputs;

[0106] When the input information bits change to ~m i When, it indicates state S i (2j) With S i+1 (8+j) Branching measure of the relationship between for:

[0107] ;

[0108] wherein ~C1 and ~C2 are the encoding outputs when the input information bits become mi.

[0109] The values of the other three branch metrics are calculated through symmetry and logical relationship:

[0110] ;

[0111] As for the branch metric calculation of the improved Viterbi algorithm, the special properties of the branch metric under specific input states are used to quickly deduce the remaining branch metrics, thereby improving the calculation efficiency

[0112] (2) Optimize the storage of path information during backtracking decoding:

[0113] When optimizing the storage of path information during backtracking decoding, the structural characteristics of convolutional codes need to be relied on. First, in the current state, the path metric with a smaller value is selected and retained as the better path. Second, the path information stored in the previous state is retrieved, and a left shift operation is performed on it, and then the highest bit data of the current state is filled in the lowest bit of the information to complete the iteration of the path information. Finally, the updated path information is stored in the storage area corresponding to the current state, completing the storage optimization.

[0114] The specific steps of the error correction result feedback stage are as follows:

[0115] (1) The receiving end checks the decoding result of the convolutional code by means of the received cumulative sum. If the cumulative sum of the original power Internet of Things sensing data received by the receiving end is different from the cumulative sum of the data obtained by the convolutional code decoding, the receiving end delivers a decoding failure feedback signal to the sending end, prompting the sending end to continue sending RS encoded data for secondary error correction.

[0116] (2) The sending end sets a waiting time If the receiving end receives a decoding failure feedback signal within the waiting time , the sending end sends RS encoded data to the receiving end.

[0117] The specific steps of the RS decoding error correction stage are as follows:

[0118] (1) Once the receiving end receives more code words, it performs convolutional code decoding on the received sequence, then connects the sequences obtained by the two convolutional decodings to form a complete RS code sequence, and performs RS decoding on it.

[0119] (2) According to the checking result of the receiving end on the decoding result, it is determined whether the received RS code word has errors. The basic principle is as follows:

[0120] Let the received polynomial y(x) received by the receiver be represented as:

[0121] ;

[0122] If the received code word has no error, the received polynomial should be divisible by the generator polynomial g(x) of the RS code, otherwise, it indicates that the received data has an error.

[0123] (3) The receiver solves the error position polynomial and the error value polynomial. After determining the error position polynomial, the error position is located by using a priority search method proposed by the application. The method is based on the path metric characteristics of Viterbi decoding, and the error position is probabilistically sorted and the search order is optimized, so as to replace the traditional money search method, thereby reducing the calculation amount and improving the decoding efficiency, and further obtaining correct data.

[0124] (4) The sending end waits for the receiving end to complete decoding and error correction.

[0125] The specific steps of the priority search proposed in the error correction result feedback stage (3) are as follows:

[0126] (1) First, calculate the path metric increment, that is, the path metric of the current shortest path is subtracted from the path metric of the shortest path before several time points, and the difference value is the path metric increment; second, calculate the path difference, that is, first determine the current shortest path and another path, and then calculate the path metric difference of the two paths, and the difference is the path difference.

[0127] (2) Locate the safe position and the unsafe position: according to the experimental statistical results, when the path difference is 2 and the path metric increment is 0, the error rate of the corresponding byte is the lowest, and this kind of position is defined as a safe position, and the remaining positions are defined as unsafe positions. According to the combination of the path metric increment and the path difference, the unsafe positions are sorted from high to low according to the error probability.

[0128] (3) Iterative search: the priority order is set as: high probability error area > second high probability error area > safe position. And according to the priority order, the elements are substituted into the error position polynomial in the priority order to determine whether it is a root. If the element is a root, the error position is found.

[0129] (4) Error value calculation and error correction

[0130] For the searched error position, the error value is calculated by using the error value polynomial algorithm, and the error value is deducted from the received sequence to restore the original power internet of things sensor data.

[0131] The effect of the power internet of things sensing data anti-tampering method of the cascaded code proposed in the patent is as shown in the accompanying Figure 6

[0132] The purpose of the present application is to propose a power internet of things sensing data anti-tampering method of cascaded code, which comprises:

[0133] (1) Propose a feedback RS-convolutional cascaded code process: including original power internet of things sensing data convolutional encoding stage, convolutional decoding and RS precoding stage, error correction result feedback stage, RS decoding error correction stage. In the original power internet of things sensing data convolutional encoding stage, the sending end sends the original power internet of things sensing data convolutional code and the cumulative sum; in the convolutional decoding and RS precoding stage, the sending end uses the improved Viterbi algorithm to decode and check the convolutional code, and the receiving end pre-encodes the original power internet of things sensing data with RS code; in the error correction result feedback stage, the sending end sends the feedback signal of the test result, and the receiving end judges whether to send the RS code encoded data for further secondary error correction according to the feedback signal; in the RS decoding error correction stage, the receiving end uses the received RS code for decoding and error correction, and uses an optimized search algorithm to improve the system performance.

[0134] (2) Improved Viterbi algorithm: through symmetry and logical relationship, the calculation process of branch metric is optimized, and the path information storage during backtracking decoding is optimized in combination with the structural characteristics of convolutional code.

[0135] (3) When decoding RS code, based on the time path metric characteristics of Viterbi decoding, the error positions are sorted by probability and the search order is optimized.

[0136] The present application proposes a power internet of things sensing data anti-tampering method of cascaded code, which mainly has the following advantages:

[0137] ​(1) Improve the efficiency and real-time performance of error correction: Through the feedback RS-convolution concatenated code process, first use convolutional code to handle random errors, and then use accumulation and check to determine whether to enable RS code correction for burst errors. Change the traditional concatenated code mode which executes complete encoding process regardless of error rate. In the low error rate scenario, reduce the redundant operation and greatly shorten the processing time. Significantly improve the real-time performance of data processing, and efficiently complete error correction in mixed error environment.(2) Optimize the decoding performance of convolutional code: Improve the Viterbi algorithm, use the special properties of branch metrics in specific input states to quickly derive the remaining branch metrics, improve the calculation efficiency; optimize the path information storage during backtracking decoding, use the structure characteristics of convolutional code to obtain the decoding result without backtracking, reduce the decoding time and storage space, and improve the decoding efficiency of convolutional code.(3) Enhance the decoding efficiency of RS code: In the RS code decoding error correction stage, based on the path metric characteristics of Viterbi decoding, the error positions are sorted by probability and the search order is optimized, the priority search method is used instead of the traditional money search method, which reduces the amount of calculation and improves the error position positioning rate, further optimizes the error correction efficiency in the RS code decoding process.

Claims

1. A tamper-proofing method for power internet of things (IoT) sensor data using concatenated codes, comprising the following steps: Step 1: convolutional encoding of raw power IoT sensor data The sending end: convolutionally encodes the data collected by the power IoT sensor and sends it to the receiving end along with the accumulated sum and state information The receiving end: receives the data from the sending end Step 2: convolutional decoding and RS precoding The sending end: RS encodes the data and processes the resulting check code word using convolutional encoding, then temporarily stores the convolutionally encoded data in the sending end The receiving end: immediately decodes the convolutional code upon receiving the data and uses the convolutional code to correct any random errors that may have occurred during transmission Step 3: error correction result feedback The receiving end: checks the decoding result of the convolutional code based on the received accumulated sum. If the accumulated sum of the raw power IoT sensor data received by the receiving end is different from the accumulated sum of the data obtained by decoding the convolutional code, the receiving end sends a decoding failure feedback signal to the sending end, prompting the sending end to continue sending RS encoded data for secondary error correction The sending end: sets a waiting period. If a decoding failure feedback signal is received from the receiving end within the waiting period, the sending end immediately transmits the RS encoded data. If no decoding failure feedback signal is received from the receiving end within the set waiting time, it is determined that no error has occurred during data transmission or that the error has been corrected by the convolutional decoding operation of the receiving end Step 4: RS decoding and error correction The receiving end: decodes the received sequence using the convolutional code, concatenates the convolutional decoding sequence, and performs RS decoding and error correction The sending end: waits for the receiving end to complete data correction 2. The power internet of things sensor data tamper-proofing method of concatenated codes of claim 1, wherein, The specific method for convolutional encoding of raw power IoT sensor data by the sending end in Step 1 is as follows: Will Each information bit is encoded bits, the convolutional code is denoted as . N represents the constraint length of the convolutional code; in Input bits at any time The output codeword is C. i (1) C i (2) ; The generating polynomial of the first code word is: ； The generating polynomial of the second code word is: ； is a variable of the generator polynomial; Subsequently, the next bit is encoded using the same method as above and the above steps are repeated to obtain a code block after convolutional encoding of the information sequence.

3. The power internet of things sensor data tamper-proofing method of concatenated codes of claim 1, wherein, The sending end RS encodes the raw power IoT sensor data in Step 2 as follows: Let the information polynomial of a set of data to be encoded be: ； represents the binary value of the k-1th bit of the group to be encoded; For RS(n, k) code over a finite field, the generating polynomial g(x) is: ； The encoding process of the RS code, i.e., the generating process of the check polynomial r(x), is as follows: ； denotes a modulo two operation; With as a symbol, the encoding polynomial is finally obtained. 。 4. The power internet of things sensor data tamper-proofing method of concatenated codes of claim 1, wherein, The specific method for using convolutional code to correct random errors that may occur during output transmission in Step 2 is as follows: Step 2.1: optimization of branch metric calculation process If the input information bit is m i , the output result of encoding is C1 and C2; if the input information bit becomes ~m i , the output of encoding will be converted to and ; assuming that the decoding input is X1, X2, the state S i (2j) at the i-th moment is transferred to the state S i+1 (j) at the i+1-th moment, and the branch metric of the transfer process is: ； The superscript j represents an index value for indicating that a pair of unique transition relations is formed by a certain input bit, represents an exclusive OR operation; When the condition "same state, input bit difference" is satisfied, the state S i (2j) branch to S i+1 (8+j) branch metric is ； Calculate the values of the other three branch metrics based on symmetry and logical relationships ； Step 2.2: optimization of path information storage during backtracking decoding When optimizing the storage of path information during backtracking decoding, rely on the structural characteristics of the convolutional code. First, in the current state, select the smaller path metric and retain it as the better path. Second, retrieve the path information stored in the previous state, perform a left shift by one bit, and then append the "highest bit data of the current state" to the lowest bit of the information to complete the iteration of the path information. Finally, store the updated path information in the storage area corresponding to the current state to complete the storage optimization.

5. The power internet of things sensor data tamper-proofing method of concatenated codes of claim 1, wherein, The method for determining decoding errors in Step 3 is as follows: Step 3.1: determine whether an error has occurred Let the received polynomial received at the receiving end be is: ； a polynomial representing the outgoing of the sending end, a polynomial representing the error causing; If the received codeword is not in error, then the received polynomial should be divisible by the generator polynomial g(x) of the RS code, otherwise, it means that the received data is in error; Step 3.2: judging error position: based on the path metric characteristics of Viterbi decoding, the error position is probabilistically sorted and the search order is optimized, the error position polynomial and the error value polynomial are solved at the receiving end, and the error position is located.

6. The power internet of things sensor data tamper-proofing method of concatenated codes of claim 1, wherein, The specific method of step 3.2 is: Step 3.2.1: extracting path metric characteristics; In the Viterbi decoding process, every time after one time instant, First, calculate the path metric increment, i.e., for each mileage... At each moment, the path metric of the current shortest path is compared with the path metric of the shortest path several moments ago. The difference is calculated, and the resulting difference is the path metric increment. Secondly, calculate the path difference, that is, first determine the current shortest path. and another path Then calculate the difference in path metrics between these two paths; this difference is the path variance. ; Step 3.2.2: locating safe position and unsafe position; When path difference is 2 and path metric increment is 0, the error rate of the corresponding byte is the lowest, and such positions are defined as safe positions, and the remaining positions are defined as non-safe positions; and the non-safe positions are sorted in descending order of error probability according to the combination of path metric increment and path difference; Step 3.2.3: iterative search; An arrangement threshold is set to distinguish a high-probability error area from a second-high-probability error area, a priority order is set as: high-probability error area > second-high-probability error area > safe position; and elements are substituted into the error position polynomial according to the priority order, and it is judged whether it is a root; if the element is a root, the error position is found; Step 3.2.4: error value calculation and error correction; For the searched error position, the error value is calculated by using the error value polynomial algorithm, and the error value is deducted from the received sequence to recover the original power internet of things sensing data.

Images